The amount of time required to train a certain number of students in some skill is usually proportional to the number of students.

In this post, I wanted to talk about a process for training people using ‘social networks’ that can work much faster and better.

The method was developed by a social start-up called Digital Green from Bangalore.

Digital Green’s mission is to educate farmers and help them improve their farm yields.

There are about 263 million people in India who depend on farming and many of them are illiterate and uneducated.

Therefore, education for farmers, if done right, can make a real difference.

Government agricultural research institutes have, for a number of years, been evolving farming best-practices, and trying to educate farmers on the same.

The government’s method of choice for educational initiatives is rural field officers who do the rounds of the villages.

But the process is often ineffective in driving change on the ground.

Digital Green discovered the reason for that.

It turned out that farmers were hesitant to abandon or change practices that had worked for their ancestors for thousands of years.

They were finding it difficult to trade time-tested ways of doing things for new methods.

Digital Green discovered that what farmers found more convincing was recommendations from early adopters from nearby villages.

They were less resistant to ideas from persons they knew.

So, Digital Green went about using their insights to change how education was delivered to farmers.

They started by constructing a social network without computers.

They made video CDs of early adopters engaging in a farming practice that needed to be promoted.

They then mailed the CDs to nearby villages – in each of which television and video equipment had been installed – and showed the videos to people there.

The farmers watching the videos would see familiar faces, places, soils and crops, and might also be tempted to adopt the practice in order to be able to star in the next video.

So, the practice would spread virally, from one early adopter to his connections, and from them to their connections, and so on.

This model of training is very similar to the model of information dissemination in social networks. Like in many other forms of viral transmission, the amount of time it takes to reach out to a certain number of people grows logarithmically with the number of people. In other words, it scales very well.

An interesting experiment has been going on in the city of Auroville (an ‘international city’ set up through a UN charter in India to promote understanding among people of different nationalities) (oh, and on the lighter side, I wonder if the internet hasn’t made Auroville totally redundant) and this experiment has been going on for about a hundred years.

The hypothesis of the founders of Auroville was that if people from different parts of the world came together and meditated together, they would enter a higher plane of consciousness, and influence humans all over the world so they would all evolve into something better than themselves, and would all realize that war was futile, and then war would become a thing of the past.

I believe they have been meditating away for the last century. I wonder what they think of the founding hypothesis of their city.

But what I found very interesting in the dream of Auroville was the idea that meditation could change the mind – could change society – could change humanity – could change the world.

Are there really tools that can change society? Are there tools for the mind?

I believe there are. I think they are:

economics

game theory

computational social science

I think that they are the tools of the mind, the tools for large-scale change, because they can be used to figure out a) what about the world needs to change, and b) how to change it.

Deciding what needs to change

A few years ago, there was a lot of discussion in India about whether corruption should be legalized. Many Indians felt that everybody was corrupt and dishonest. So, if we were all doomed to dishonesty, why fight the reality of our existence? So some chap asked the question – why should we not legally sanction corruption, and make corruption ok?

Given a question like that, you can use the three tools I have listed to come up with an answer.

It turns out that it would be a terrible idea to legalize corruption.

And the answer comes from economics, as the following example will show.

There are really two models of corruption.

Both as you will see, can be harmful.

Speed-Money Corruption

In India, bureaucrats sometimes deliberately delay the processing of applications in the hope of getting a bribe to move the file along. A citizen who needs, let’s say a water connection, has to pay a bribe to a clerk to get their application looked at.

This seems like a fairly harmless form of corruption (some people defend it as necessary in a free market, as a mechanism for the differentiation of services).

But if you take a closer look and think about the economics of it, you see that what is being demonstrated is a form of rent-seeking behaviour. And you will see that it has the harmful side-effect of encouraging inefficiency.

As time progresses, the processes get slower and slower and newer hurdles and pain points are introduced to make people fork out more and more money, and everyone ends up losing – paying a heavy price for encouraging such practices – because of the resulting inefficiencies.

Just remember one point here. This form of corruption rewards the least efficient worker.

Man-In-The-Middle Corruption

The second kind of corruption is the man-in-the-middle kind of corruption. This is the corruption you encounter when people’s money passes through the hands of a middle-man tasked with procuring services for them.

In the realm of public services, like the construction of roads and schools, that middle-man is government.

In the presence of corruption, the middle-man ends up selecting the service-provider who pays the highest bribes, not the service-provider who does the best job.

This leads to a market where the lowest-quality service provider wins and the higher quality providers leave the market altogether.

This last bit is actually an application of economic theory.

It follows from the work of George A. Akerlof. He described it in a paper titled ‘The Market for “Lemons”: Quality Uncertainty and the Market Mechanism’.

So, we see that using economics theory, we can show that it would be a terrible idea to legalize corruption.

You can also change lives, society, and humanity using these tools.

Example of use in bringing about change

Some months back, we had written an article about poverty in India. We came up with a model to describe possible causes of poverty, and suggested a solution. The solution required the use of algorithmic complexity theory.

Game theory and computational social science are useful as well.

Game theory was the subject of the research of the two Nobel Prize winners of 2012 – Alvin Roth and Lloyd Shapley.

In a BBC article on Roth and Shapley the economics editor of the BBC, Stephanie Flanders is quoted as saying “In the past 50 years, game theorists – and micro-economics in general – have genuinely made the world a better place”.

Again, quoting Stephanie, “Mr Roth helped New York City redesign its system for allocating children to public school places”.

Finally, on to the really new field of computational social science. This is a field that has only been in existence for around 10 years now.

Here is an excellent article in Nature about computational social science. In the article, a computational social scientist by the name of Kleinberg, from Cornell, Ithaca, is quoted as saying: “I realized that computer science is not just about technology. It is also a human topic.”

Some of the papers Kleinberg has written include ‘How bad is forming your own opinion?’ and ‘You had me at hello: how phrasing affects memorability’.

It’s almost a year since the attacks took place, and we thought we’d finally write about our work on the problem (which we’ve shared with many government organizations, including CAIR, though we frankly don’t know if they plan to implement it).

Introduction:

When multiple coordinated attacks take place (like the three bombs that were triggered simultaneously in three locations in Mumbai in 2011), if the attackers had used cell phones to coordinate their attacks, the phone numbers involved can be extracted mathematically from the call records linked to the cell towers in the vicinity of the attacks.

Our calculations indicate that in a city the size of Mumbai and a population of around 20 million people, you would need a minimum of only 3 simultaneous attacks to be able to pinpoint the attackers to within 1 person. If there were only 2 attacks, you would have a much higher uncertainty. The greater the number of coordinated attacks, the easier it is to identify the attackers.

The identification will only be possible if the attackers used their cell phones to coordinate with a central handler, or with each other, or a group of handlers who in turn communicated with each other. It would be possible to support different possible patterns of communication and usage of cell phones and SMS to coordinate between the attackers and confirm the attacks.

History:

A similar method might have already been used in Europe after the Madrid bombings to identify those responsible for the same.
Two years after the attacks, the EU mandated that carriers store some details for 6 months. The information that the carriers need to preserve contains all the details required to triangulate attackers in multiple simultaneous attacks.

Here is some information on the directive from the Wikipedia:

—

On 15 March 2006 the EU formally adopted Directive 2006/24/EC, on “the retention of data generated or processed in connection with the provision of publicly available electronic communications services or of public communications networks and amending Directive 2002/58/EC.”

The Directive requires Member States to ensure that communications providers must retain, for a period of between 6 months and 2 years, necessary data as specified in the Directive.

 to trace and identify the source of a communication;
 to trace and identify the destination of a communication;
 to identify the date, time and duration of a communication;
 to identify the type of communication;
 to identify the communication device;
 to identify the location of mobile communication equipment.

The data is required to be available to competent national authorities in specific cases, “for the purpose of the investigation, detection and prosecution of serious crime, as defined by each Member State in its national law”.

—

Information:

The minimum information that would be needed to obtain an effective fix on an attacker is the following:
a) FROM_NUMBER
b) TO_NUMBER
c) TIME_STAMP
d) CELL_TOWER

Indian carriers tend to store the FROM, TO and TIME information in call logs (used by the carriers for billing and for customer service) for SMS messages for 2 days and for phone calls for 30 days. These can be obtained easily from them by a simple request from police.
The location of the cell tower is determined from signaling logs.

Technology:

Messages used to coordinate teams have certain patterns. For example, a possible pattern in an attack is a confirmation – success/failure – to the central handler after an attack.

Each message would have to originate from a cell tower near the site of a blast and in a short time window after the blast and have the same destination.

Out of all the hundreds of millions of messages sent in a city, only some would satisfy all these constraints.
Simple graph analysis can identify these messages, to very high accuracies in a city of 20 million of the size of Mumbai, provided there were 3 or more coordinated attacks.

The algorithm is so simple that an undergraduate student could build it in a few months.

Acknowledgements:

There are many people I have to thank for their help with this study, including old mentors from other research firms in the area who helped me with suggestions for handling temporal queries, and students/interns who helped speed up the study, and my colleague Sumukh who works on graph/tree search himself.